activity
20192024
most citedDeep Learning Based Channel Covariance Matrix Estimation with User Location and Scene Images

40 citations · 47 across the 7 of their papers we have counts for

collaborators

7 papers

eess.SP2024

Corrections to "Computer Vision Aided mmWave Beam Alignment in V2X Communications"

Weihua Xu, Feifei Gao, Xiaoming Tao +2

In this document, we revise the results of [1] based on more reasonable assumptions regarding data shuffling and parameter setup of deep neural networks (DNNs). Thus, the simulatio…

eess.SP2023

Multi-User Matching and Resource Allocation in Vision Aided Communications

Weihua Xu, Feifei Gao, Yong Zhang +2

Visual perception is an effective way to obtain the spatial characteristics of wireless channels and to reduce the overhead for communications system. A critical problem for the vi…

eess.SP2023

Vision Aided Environment Semantics Extraction and Its Application in mmWave Beam Selection

Feiyang Wen, Weihua Xu, Feifei Gao +2

In this letter, we propose a novel mmWave beam selection method based on the environment semantics extracted from user-side camera images. Specifically, we first define the environ…

eess.SP2022

Vision-Aided Blockage Avoidance in UAV-assisted V2X Communications

Ruijin Ding, Weihua Xu, Wanmai Yuan +1

The blockage is a key challenge for millimeter wave communication systems, since these systems mainly work on line-of-sight (LOS) links, and the blockage can degrade the system per…

eess.SP2022★ 4 cited

Computer Vision Aided mmWave Beam Alignment in V2X Communications

Weihua Xu, Feifei Gao, Xiaoming Tao +2

Visual information, captured for example by cameras, can effectively reflect the sizes and locations of the environmental scattering objects, and thereby can be used to infer commu…

eess.SP2021★ 40 cited

Deep Learning Based Channel Covariance Matrix Estimation with User Location and Scene Images

Weihua Xu, Feifei Gao, Jianhua Zhang +2

Channel covariance matrix (CCM) is one critical parameter for designing the communications systems. In this paper, a novel framework of the deep learning (DL) based CCM estimation…

eess.SP2019★ 3 cited

3D Scene Based Beam Selection for mmWave Communications

Weihua Xu, Feifei Gao, Shi Jin +1

In this paper, we present a novel framework of 3D scene based beam selection for mmWave communications that relies only on the environmental data and deep learning techniques. Diff…